Adaptive multivariate fault detection

A multi-variable statistical and error technology, applied in the field of error detection, can solve problems such as inaccurate statistical values, false alarms and failures, and failure to provide coordination

Inactive Publication Date: 2009-05-20
APPLIED MATERIALS INC
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  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

However, by adjusting only univariate means and scaling coefficients, this method cannot provide adjustment of these covariances among variables within a model
[0011] Each of the common adaptation methods described above is susceptible to cumulative computational rounding errors caused by the periodic adaptation
This then results in the model having imprecise statistics which can cause both false alarms and failures to detect errors

Method used

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  • Adaptive multivariate fault detection
  • Adaptive multivariate fault detection
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Embodiment Construction

[0068] Described herein is a method and apparatus for detecting errors. In one embodiment, process data comprising a plurality of process variables is received. Examples of process variables include temperature, pressure, silane flow, and the like. One or more multivariate statistical models are adapted based on the processed data. Adapting can include applying a change to at least one univariate statistic of the multivariate statistic module if the change will not exceed a threshold. In an embodiment, adaptation is performed over predetermined intervals based on a measured drift of one or more process variables. The adapted multivariate statistical model can then be used to analyze subsequent processing data for the detection of each error.

[0069] In the following description, numerous details are set forth. However, it will be apparent to those skilled in the art that the present invention may be practiced without the following specific details. In certain instances, ...

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Abstract

A method and apparatus for detecting faults. A set of data samples is received, the set of data samples including multiple process variables. One or more multivariate statistical models are adapted, wherein adapting includes applying a change to at least one univariate statistic of the one or more multivariate statistical models if the change is greater than a threshold value. The one or more multivariate statistical models are used to analyze subsequent process data to detect faults.

Description

[0001] related application [0002] This application claims priority to Provisional Application No. 60 / 746649, filed May 7, 2006, and Provisional Application No. 60 / 746647, filed May 7, 2006. technical field [0003] Particular embodiments of the present invention relate to error detection, and more particularly to error detection using multiple error signatures. Background technique [0004] Many businesses employ sophisticated manufacturing equipment that includes multiple sensors and controls that are carefully monitored during processing to ensure product quality. One method of monitoring these multiple sensors and controllers is statistical process monitoring (a means of performing statistical analysis on sensor measurements and process control values ​​(process variables)), which enables automatic detection and / or error detection . A "fault" can be a malfunction or misalignment of manufacturing equipment (such as a deviation of an operating parameter of a machine fro...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F11/30G06F17/18
Inventor J·L·小哈维A·T·施沃姆
Owner APPLIED MATERIALS INC
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